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IJMSInternational Journal of Molecular Sciences
  • Review
  • Open Access

5 January 2026

Cognition, Cytokines, Blood–Brain Barrier, and Beyond in COVID-19: A Narrative Review

,
,
and
1
Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, Bellatera, 08193 Cerdanyola del Vallès, Spain
2
Serra Húnter Programme, Government of Catalonia, 08002 Barcelona, Spain
3
Psiquiatria Molecular, Institut de Recerca Sant Joan de Déu, Parc Sanitari Sant Joan de Déu, 08830 Sant Boi de Llobregat, Spain
4
Departamento de Ciencias Biológicas y Químicas, Facultad De Ciencias, Universidad San Sebastián, Sede Tres Pascualas Lientur 1457, Concepción 4080871, Chile
This article belongs to the Section Molecular Neurobiology

Abstract

Numerous studies report cognitive impairment in COVID-19 patients from the acute to post-acute phases, linked to blood inflammation affecting blood–brain barrier (BBB) permeability and causing leakage of glial and neuronal proteins. However, a clear classification of these cognitive deficits and molecular blood events over time is still lacking. This narrative review summarizes the neuropsychological consequences of COVID-19 and evidence of altered cytokines and BBB disruption as potential mediators of cognitive impairment across post-infection phases. Post-COVID-19 cognitive dysfunction appears to follow a temporal course, evolving from acute focal deficits in attention, working memory, and executive function to more persistent multidomain impairments. We reviewed key cytokines released into the blood during COVID-19 infection, including antiviral (IFNγ, CXCL1, CXCL10), inflammatory (IL-1β, IL-2, IL-4, IL-6, IL-7, IL-8, IL-10, GM-CSF, TNFα), and monocyte chemoattractants (MCP1/CCL2, MCP3/CCL7, MIP-1α/CCL3, GM-CSF, G-CSF). This analysis shows that several inflammatory and viral cytokines remain elevated beyond the acute phase and are associated with cognitive deficits, including IL-6, IL-13, IL-8, IL-1β, TNFα, and MCP1 in long-term post-COVID-19 patients. In addition, we examined studies analyzing changes over time in neurovascular unit proteins as biomarkers of BBB disruption, including extracellular matrix proteins (PPIA, MMP-9), astrocytes (S100β, GFAP), and neurons (NFL). These proteins are elevated in acute COVID-19 but generally return to control levels within six months, suggesting BBB restoration. However, in patients followed for over a year, BBB disruption persists only in those with cognitive impairment and is associated with systemic inflammation, with TGFβ as a related biomarker. Although cognitive sequelae can persist for over 12 months after SARS-CoV-2 infection, further studies are needed to investigate long-term neurocognitive outcomes and their link to sustained proinflammatory cytokine elevation and brain impact.

1. Introduction

The coronavirus (SARS-CoV-2) that causes coronavirus disease (COVID-19) was first identified in Wuhan City, Hubei Province, China, on 29 December 2019 [1]. It was declared a pandemic by the World Health Organization (WHO) on 11 March 2020 and rapidly spread throughout the world, resulting in devastating illness, mortality, and broad public health implications [2]. Over 778 million cases and 7.1 million deaths have been recorded worldwide since December 2019, but the actual number is thought to be higher. The number of cases increased partly due to new variants, such as EG.5 and BA.286 [3]. Thus, a large proportion of the world’s population has been exposed to this viral infection, and the health consequences in the short, medium, and long term need to be analyzed in the post-pandemic COVID-19 era.
One of the health problems early reported in many survivors was cognitive complaints that appear to endure and may potentially worsen over time in susceptible individuals [4,5]. These manifestations have been described as “brain fog”, an umbrella and informal term that has been used to explain the constellation of cognitive domains involved [4]. The accumulated evidence in the literature has reported multiple cognitive impairments in COVID-19 survivors [6]. However, a clear classification of these cognitive impairments across the infection, recovery, and post-COVID-19 phases at different stages has not been addressed yet.
Different potential mechanisms by which SARS-CoV-2 infection could explain the development of these neurocognitive impairments in COVID-19 have been speculated, among them is an exacerbated inflammatory response, considered a feature of severe COVID-19 patients with acute respiratory distress [7,8,9]. Initially, a broad mechanism responsible for these cognitive difficulties postulated direct viral damage of the cortex and adjacent subcortical structures and indirect effects due to non-Central Nervous System (CNS) systemic impairment [10]. In this regard, direct CNS infection, systemic and neuroinflammation, and prolonged hypoxia have been proposed as contributors to both acute and post-acute cognitive manifestations of COVID-19 [11]. Later studies found different neurological correlates linked to cognitive impairments, as microvascular damage following the hypercoagulable phase, neuroinflammation and white matter abnormalities in frontal and parietal lobes, and frontoparietal hypometabolism [6], providing brain structural and functional alterations that could underlie the cognitive sequelae of COVID-19. Nevertheless, the relationship between SARS-CoV-2-induced inflammation and cognitive impairments in patients with COVID-19 remains to be elucidated.
In SARS-CoV-2 infection, there is an increased release of cytokines in blood plasma from lung tissue caused by a dysfunctional immune response [7]. Pyroptosis, a highly inflammatory form of programmed cell death of cytopathic virus as SARS-CoV-2 [12], of epithelial cells causes an initial release of IL-1β into the blood [13]. Local inflammation in the lung leads to the production of IL-6, IFNγ, Monocyte Chemoattractant Protein-1 (MCP1), and Interferon gamma-induced Protein 10 (IP-10) from T helper 1 polarized cells and the secretion of these cytokines and chemokines into the blood in SARS-CoV-2 patients [13] to attract monocytes and T lymphocytes to lung tissue [14] and, in most cases, help to resolve the infection. However, in some patients there is an exacerbated release over time of IL-6, IL-10, IL-2, IL-7, granulocyte-macrophage colony-stimulating factor (GM-CSF), IP-10, MCP1, macrophage inflammatory protein 1α (MIP1α), and tumor necrosis factor α (TNFα) into the blood [7,15]. This cytokine storm and chemokines MCP1 and MIP1α are suggested to be produced by different subpopulations of monocytes [16,17]. Thus, an exacerbated release of cytokines occurs during infection. Many studies have also reported that some cytokines are also elevated after recovery [18]; however, a global picture of the cytokine profile at different phases, during infection and, more importantly, after recovery is not clear in the literature.
In the initial phases of the COVID-19 pandemic, the direct entrance of the virus into the brain was proposed [19,20], based on the fact that multiple cell types (neurons, endothelial cells, microglia, and astrocytes) in the CNS expressed the angiotensin-converting enzyme 2 (ACE2) receptor on its surface facilitating the entry of the virus into the nervous system [21,22]. Later, it was confirmed that one pathway through which SARS-CoV-2 virus transits across the Blood–Brain Barrier (BBB) was brain microvascular endothelial cells, a cellular component of the neurovascular unit of this barrier [23]. Histopathological studies in the human postmortem brain from subjects infected with SARS-CoV-2 demonstrated the presence of activated microglia and infiltration by cytotoxic T lymphocytes in 79% of patients [24]. In this study, the virus was found in 53% of the brains analyzed. However, although the detection of the virus in the brain was found in a large proportion of the brains of deceased COVID-19 patients, the presence of the virus was not associated with the severity of the neuropathological changes identified [24], suggesting that other indirect mechanisms could be responsible for these anatomopathological changes. Indeed, peripheral SARS-CoV-2-associated cytokines, IL-6, IL-1β, and TNFα, were known to be capable of disrupting the BBB [25]. Altered BBB permeability induces neuroinflammation by activating astrocytes and microglia. The astrocytic cytokine protein S100β could pass through the damaged BBB and be detected in peripheral blood [26]. Metalloproteases from the extracellular matrix of BBB, such as the matrix metalloprotease 9 (MMP-9), degrade proteins of endothelial tight junctions and the basal membrane, altering BBB permeability [27] and facilitating the infiltration of leukocytes in other coronavirus infections and its detection in blood [28,29]. Cytokines such as TNFα and IL-1β are involved in multiple mechanisms that regulate MMPs, altering BBB permeability [27]. Thus, altogether, this suggest that biomarkers of BBB disruption could be detected also in the blood of COVID-19 patients. Indeed, some studies have reported the presence of proteins of the neurovascular unit in blood in COVID-19 patients [30,31]. However, a detailed overview of biomarkers of BBB disruption over time in COVID-19 is still unavailable in the literature.
This narrative review aims to collect the reported neuropsychological repercussions of COVID-19 disease, and evidence of altered cytokines and BBB disruption as potential mediators of impaired cognition over time. Thus, the following issues are included: (i) the neuropsychological consequences of COVID-19 at different stages; (ii) the temporal profile of altered cytokines and biomarkers of blood–brain barrier (BBB) disruption during and after SARS-CoV-2-infection; and (iii) the influence of these cytokines and BBB biomarkers on cognitive processes.
It is important to note the heterogeneity of terminology across studies, as terms such as “long COVID,” “post-acute sequelae,” and “post-COVID condition” are often used interchangeably to describe similar persistent symptoms. To ensure clarity, definitions of each term are provided when they first appear in this review, while preserving the original language used in the cited studies.

3. Conclusions

Based on the analysis of the evidence compiled in this review, post-COVID-19 cognitive dysfunction exhibits a distinctive temporal evolution, marked by the transition from an acute focal and functional deficit, whose primary etiology is thought to involve systemic neuroinflammation and BBB disruption, to a chronic multidomain pattern, indicating sustained neurobiological pathology.
In the acute phase (weeks 1–4), the pattern is focal, affecting higher-order cognitive functions such as executive function, memory, and attention, but it does not align with a neurodegenerative decline, as findings suggest acute and transient inflammatory mechanisms. This trend persists in post-acute phase I (weeks 5–12), where a dysexecutive pattern is consolidated, with particular vulnerability in cognitive control, attention, and working memory. The etiology at this stage remains primarily linked to systemic clinical factors (hypoxia, inflammation) rather than structural damage.
However, in post-acute phase II (weeks 13–24) and even stronger in post-acute phase III (more than 24 weeks), although the pattern maintains a clear multidomain emphasis on attention and executive functions, the deficit typology begins to show possibly more persistent underlying mechanisms. The chronicity and high prevalence of long-term deficits, along with the evidence of neurobiological alterations (reduction in volume in certain brain regions and elevation of neuronal damage biomarkers), suggest that, while the initial phase was transient, the persistent deficits could be associated with neuronal or glial damage that more closely resembles a process of sustained deterioration, distinct from the acute decline that will require a long-term rehabilitative approach.
In this context, to elucidate the underlying biological mechanisms contributing to post-COVID cognitive deficits, this review has focused its analysis on evidence pertaining to two key biological pathways that may be implicated in the pathogenesis of these sequelae following SARS-CoV-2 infection. We analyzed the existing evidence for some of the most relevant cytokines released into the blood upon infection in three categories: antiviral (IFNγ, CXCL1, CXCL10), inflammatory (IL-1β, IL-6, IL-10, IL-2, IL-4, IL-7, IL-8, and TNFα), and monocyte chemoattractant proteins (MCP1, also called CCL2, and MCP3, also called CCL7), as well as MIP-1α, also called CCL3, GM-CSF, and G-SCF. We provide a specific profile of antiviral and inflammatory cytokines and chemoattractant proteins that have been reported across different temporal phases in the acute phase, with some of them related to a neurological clinical phenotype and severely ill COVID-19 patients. This temporal analysis highlights the persistence of altered viral and inflammatory cytokines beyond the acute infection phase, which remain elevated and linked to cognitive deficits even in the longest phase analyzed with several studies exceeding one-year post-infection. In this regard, a relevant observation is the consistency of the elevation of inflammatory cytokines IL-6, IL-13, IL-8, IL-1β, and TNFα at the longest phase of follow-up related to cognitive deficits and/or post-acute sequelae. MCP1 was also elevated in this long-term phase in patients with cognitive impairment.
In addition, using the same design, we also analyzed the evolutionary changes over time of proteins of the neurovascular unit as a biomarker of BBB disruption: proteins of the extracellular matrix (PPIA and MMP-9), astrocytes (S100β and GFAP), and neurons (NfL) were detectable in blood samples from COVID-19 patients in the acute phase, and in the subsequent phases, they were reduced until they reach the control levels, suggesting that the initial leakage of BBB seems to be restored during the next 6 months. However, a follow-up period longer than one year identified that BBB disruption is restricted to a particular clinical phenotype linked with cognitive impairment and related to systemic inflammation providing TGFβ as a biomarker related to the degree of BBB disruption.

3.1. Clinical Implications

The evolutionary nature of post-COVID-19 cognitive dysfunction, which progresses from a transient deficit to a possible involvement of more persistent mechanisms, poses fundamental clinical implications for its management. Similar trajectories of cognitive impairment have been observed following other viral infections, providing context for the post-COVID-19 sequelae. For instance, influenza infections have been associated with long-term neurological effects, likely mediated by systemic inflammation and central nervous system dysfunction even without direct neurotropism, suggesting partially overlapping mechanisms with post-COVID-19 outcomes [82]. Neuroinvasive arbovirus infections, such as West Nile virus, can also lead to persistent memory and other cognitive deficits [83], while case series of Epstein–Barr virus encephalitis show that some patients experience long-lasting cognitive, sensory, and motor dysfunctions after acute recovery [84]. These observations indicate that prolonged cognitive impairments are not unique to COVID-19, underscoring the importance of early identification, continuous monitoring, and the implementation of sustained neurocognitive rehabilitation strategies.
All the evidence reported in this review indicates that cognitive impairment occurs significantly in the symptomatic phases, both acute and post-acute, of COVID-19 patients. This initial focal and dysexecutive pattern (acute phase and post-acute phase I) shows the urgent need for detailed neuropsychological evaluations to identify vulnerabilities in higher-order functions (executive function, attention). In view of these results, it seems appropriate to offer, as soon as possible, rehabilitation therapies focused on training strategies to allow for the restoration of the deficit rather than its compensation, as well as to facilitate independence in activities of daily living. However, the evidence of chronicity and the high prevalence of multidomain deficits in post-acute phases II and III, coupled with the findings of neurobiological alterations suggesting a process of sustained damage, requires that this rehabilitation approach be long-term and multidimensional. This approach must combine specific cognitive rehabilitation (focused on attentional and executive training) with the treatment of coexisting affective symptoms (such as depression and anxiety) and continuous medical follow-up to manage the chronic functional and occupational impact, all of which are crucial to facilitate a complete functional recovery. Although some studies with beneficial results already point in this direction [46], these have primarily focused on the rehabilitation of cognitive functions in patients who suffered severe COVID-19 illness with relevant cognitive decline.
Nowadays, neurocognitive rehabilitative treatments are not considered a priority in the treatment of COVID-19 survivors. Nevertheless, a remarkable aspect of COVID-19 patients, after recovering from infection, is that many express cognitive complaints together with a variety of subtle symptoms; however, since these deficits are not severe, not enough attention has been paid yet by the exhausted health care system. A concern in the field is that these patients are at high risk of transiting to a chronic altered cognitive state to compensate for these deficits instead of restoring them at the right time. For this reason, there is a current and urgent need in the post-COVID-19 era not only to deepen research into the clinical sequelae of survivors of SARS-CoV-2 infection over the long term but also establish long-term cognitive rehabilitation therapies for post-COVID-19 patients.
In addition, a complete neuropsychological assessment of COVID-19 patients should be considered to carry out a personalized rehabilitation intervention. The assessment should include the administration of tests that accurately evaluate cognitive functions that previous studies referenced in this review have reported as impaired domains, mainly executive function and attention, but also verbal memory, working memory, verbal fluency, processing speed, and visuospatial skills. As described by Sozzi et al. [85], neuropsychological assessment cannot be considered as the mere administration of psychometric tests. It should provide a profile of residual abilities, emerging difficulties, and a potential trend of cognitive decline. In addition, the assessment of COVID-19 patients cannot be limited to the administration of screening batteries, whenever a patient’s clinical condition allows it.
The characterization of the long-term cognitive profile in COVID-19 patients is needed to further provide personalized therapeutic interventions based on this profile. The benefit for the patients is clear because by knowing the cognitive domain to be restored, a personalized therapeutical strategy will be administered. Further studies addressing the long-term consequences of COVID-19 on cognition will also provide robust tools for the health system to identify patients at high risk of cognitive sequelae. Prevention programs focused on detecting future cognitive decline in this population must be launched based on these studies.
Another remarkably relevant aspect still unexplored is the question of whether having suffered a SARS-CoV-2 infection could produce a subtle chronic peripheral inflammation after one or two years of acute phase compared to unaffected individuals and whether this possible subtle chronic inflammation is related to cognitive deficits. This information is necessary to determine the usefulness or not of early anti-inflammatory treatment post-recovery to prevent cognitive sequelae.

3.2. Future Research

The relevance of this topic is crucial in the post-pandemic era. While the current evidence confirms cognitive deficits and establishes a profile in the acute and post-acute phases, there is a current and urgent need to sustain research efforts on these sequelae to offer effective and specific treatments.
The scientific agenda must focus on addressing major knowledge gaps, the main one being the question of whether COVID-19 patients develop long-term neuropsychological sequelae (beyond three years) and whether these sequelae correlate with the degree of inflammatory cytokine release into the bloodstream at the time of infection. It is vital to investigate how this exacerbated cytokine overproduction affects cognition, especially in mental health patients with pre-existing immune or neuroinflammatory dysfunction. Another critical line of inquiry is to delve into the disruption of the BBB in chronic phases. Although the initial disruption appears to resolve, research is needed to investigate which patient subgroups maintain long-term BBB compromise (e.g., those with persistent TGFβ elevation) and how this sustained alteration contributes to neuronal and glial damage. Furthermore, it remains a critical aspect to explore whether the cognitive profile is dependent on the illness phase and what risk or protective factors (comorbidities, cognitive reserve) are related to the onset and persistence of deficits.
To address these questions, longitudinal studies expected between two and four years post-infection must be designed with notably improved protocols. These protocols must go beyond preliminary studies and include comparisons between different severity groups based on unified clinical classifications and terminologies; age- and sex-balanced groups; clearly defined temporal phases (based on the first positive PCR); and the specification of the viral strain to which these patients were exposed. Cognitive assessment instruments must be more comprehensive, covering core deficits such as attention and executive function and tracking subjective complaints that emerge due to different psychopathological mechanisms.
Finally, future research must move toward intervention. It is fundamental not only to continue exploring the impact of COVID-19 on the brain and its underlying causes but also to promote urgent clinical trials to establish personalized therapies based on the molecular and cognitive profiles of patients.

Author Contributions

Conceptualization, A.B. and B.R.; formal analysis, A.B., B.R., G.R.-A. and A.V.-M.; writing—original draft preparation, A.B. and B.R.; writing—review and editing, A.B., B.R., G.R.-A. and A.V.-M.; visualization, A.B. and B.R.; supervision, A.B. and B.R.; funding acquisition, B.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Instituto de Salud Carlos III, grant number PI21/00059 to B.R.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Acknowledgments

During the preparation of this manuscript, the authors used Chat GPT (OpenAI; GPT-4), https://chat.openai.com, accessed 1 October 2025, in some instances to synthesize sections of the original text and for grammar and spelling revision. The authors have reviewed and edited all generated content and take full responsibility for the content of this publication.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
COVID-19Coronavirus disease 19
GM-CSFGranulocyte-macrophage colony-stimulating factor
ILInterleukin
INFInterferon
IP-10Interferon gamma-induced protein 10
MCP1Monocyte chemoattractant protein-1
MIP1αMacrophage inflammatory protein 1α
MMPMatrix metalloprotease protein
PPIAPeptidyl prolyl cistrans isomerase A
SARS-CoV-2Severe acute respiratory syndrome coronavirus 2
TGFβTumor growth factor β
TNFαTumor necrosis factor α

References

  1. Chen, N.; Zhou, M.; Dong, X.; Qu, J.; Gong, F.; Han, Y.; Qiu, Y.; Wang, J.; Liu, Y.; Wei, Y.; et al. Epidemiological and Clinical Characteristics of 99 Cases of 2019 Novel Coronavirus Pneumonia in Wuhan, China: A Descriptive Study. Lancet 2020, 395, 507–513. [Google Scholar] [CrossRef]
  2. Rabinovitz, B.; Jaywant, A.; Fridman, C.B. Neuropsychological Functioning in Severe Acute Respiratory Disorders Caused by the Coronavirus: Implications for the Current COVID-19 Pandemic. Clin. Neuropsychol. 2020, 34, 1453–1479. [Google Scholar] [CrossRef]
  3. World Health Organization. Coronavirus Disease (COVID-19). 2023. Available online: https://www.who.int/news-room/fact-sheets/detail/coronavirus-disease-(covid-19) (accessed on 28 July 2025).
  4. Nouraeinejad, A. Brain Fog as a Long-Term Sequela of COVID-19. SN Compr. Clin. Med. 2023, 5, 9. [Google Scholar] [CrossRef]
  5. Jason, L.A.; Islam, M.; Conroy, K.; Cotler, J.; Torres, C.; Johnson, M.; Mabie, B. COVID-19 Symptoms Over Time: Comparing Long-Haulers to ME/CFS. Fatigue 2021, 9, 59–68. [Google Scholar] [CrossRef]
  6. Perrottelli, A.; Sansone, N.; Giordano, G.M.; Caporusso, E.; Giuliani, L.; Melillo, A.; Pezzella, P.; Bucci, P.; Mucci, A.; Galderisi, S. Personalized Medicine Systematic Review Cognitive Impairment after Post-Acute COVID-19 Infection: A Systematic Review of the Literature. J. Pers. Med. 2022, 12, 2070. [Google Scholar] [CrossRef]
  7. Tay, M.Z.; Poh, C.M.; Rénia, L.; MacAry, P.A.; Ng, L.F.P. The Trinity of COVID-19: Immunity, Inflammation and Intervention. Nat. Rev. Immunol. 2020, 20, 363–374. [Google Scholar] [CrossRef]
  8. Gao, Y.M.; Xu, G.; Wang, B.; Liu, B.C. Cytokine Storm Syndrome in Coronavirus Disease 2019: A Narrative Review. J. Intern. Med. 2021, 289, 147–161. [Google Scholar] [CrossRef]
  9. Choi, H.; Shin, E.C. Hyper-Inflammatory Responses in COVID-19 and Anti-Inflammatory Therapeutic Approaches. BMB Rep. 2022, 55, 11–19. [Google Scholar] [CrossRef]
  10. Ritchie, K.; Chan, D.; Watermeyer, T. The Cognitive Consequences of the COVID-19 Epidemic: Collateral Damage? Brain Commun. 2020, 2, fcaa069. [Google Scholar] [CrossRef]
  11. Steardo, L.; Steardo, L.J.; Zorec, R.; Verkhratsky, A. Neuroinfection May Contribute to Pathophysiology and Clinical Manifestations of COVID-19. Acta Physiol. 2020, 229, e13473. [Google Scholar] [CrossRef]
  12. Fink, S.L.; Cookson, B.T. Apoptosis, Pyroptosis, and Necrosis: Mechanistic Description of Dead and Dying Eukaryotic Cells. Infect. Immun. 2005, 73, 1907–1916. [Google Scholar] [CrossRef]
  13. Huang, C.; Wang, Y.; Li, X.; Ren, L.; Zhao, J.; Hu, Y.; Zhang, L.; Fan, G.; Xu, J.; Gu, X.; et al. Clinical Features of Patients Infected with 2019 Novel Coronavirus in Wuhan, China. Lancet 2020, 395, 497–506, Erratum in Lancet 2020, 395, 496. [Google Scholar] [CrossRef]
  14. Xu, Z.; Shi, L.; Wang, Y.; Zhang, J.; Huang, L.; Zhang, C.; Liu, S.; Zhao, P.; Liu, H.; Zhu, L.; et al. Pathological Findings of COVID-19 Associated with Acute Respiratory Distress Syndrome. Lancet Respir. Med. 2020, 8, 420–422, Correction in Lancet Respir. Med. 2020, 8, e26. [Google Scholar] [CrossRef]
  15. Gubernatorova, E.O.; Gorshkova, E.A.; Polinova, A.I.; Drutskaya, M.S. IL-6: Relevance for Immunopathology of SARS-CoV-2. Cytokine Growth Factor. Rev. 2020, 53, 13–24. [Google Scholar] [CrossRef]
  16. Liao, M.; Liu, Y.; Yuan, J.; Wen, Y.; Xu, G.; Zhao, J.; Cheng, L.; Li, J.; Wang, X.; Wang, F.; et al. Single-Cell Landscape of Bronchoalveolar Immune Cells in Patients with COVID-19. Nat. Med. 2020, 26, 842–844. [Google Scholar] [CrossRef]
  17. Zhou, Y.; Fu, B.; Zheng, X.; Wang, D.; Zhao, C.; Qi, Y.; Sun, R.; Tian, Z.; Xu, X.; Wei, H. Pathogenic T-Cells and Inflammatory Monocytes Incite Inflammatory Storms in Severe COVID-19 Patients. Natl. Sci. Rev. 2020, 7, 998–1002. [Google Scholar] [CrossRef]
  18. Diamanti, A.P.; Rosado, M.M.; Pioli, C.; Sesti, G.; Laganà, B. Cytokine Release Syndrome in COVID-19 Patients, a New Scenario for an Old Concern: The Fragile Balance between Infections and Autoimmunity. Int. J. Mol. Sci. 2020, 21, 3330. [Google Scholar] [CrossRef]
  19. Fenrich, M.; Mrdenovic, S.; Balog, M.; Tomic, S.; Zjalic, M.; Roncevic, A.; Mandic, D.; Debeljak, Z.; Heffer, M. SARS-CoV-2 Dissemination Through Peripheral Nerves Explains Multiple Organ Injury. Front. Cell Neurosci. 2020, 14, 229. [Google Scholar] [CrossRef]
  20. Yachou, Y.; El Idrissi, A.; Belapasov, V.; Ait Benali, S. Neuroinvasion, Neurotropic, and Neuroinflammatory Events of SARS-CoV-2: Understanding the Neurological Manifestations in COVID-19 Patients. Neurol. Sci. 2020, 41, 2657–2669. [Google Scholar] [CrossRef]
  21. Zubair, A.S.; McAlpine, L.S.; Gardin, T.; Farhadian, S.; Kuruvilla, D.E.; Spudich, S. Neuropathogenesis and Neurologic Manifestations of the Coronaviruses in the Age of Coronavirus Disease 2019: A Review. JAMA Neurol. 2020, 77, 1018–1027. [Google Scholar] [CrossRef]
  22. Wang, Q.; Zhang, Y.; Wu, L.; Niu, S.; Song, C.; Zhang, Z.; Lu, G.; Qiao, C.; Hu, Y.; Yuen, K.-Y.; et al. Structural and Functional Basis of SARS-CoV-2 Entry by Using Human ACE2. Cell 2020, 181, 894–904.e9. [Google Scholar] [CrossRef]
  23. Chen, Y.; Yang, W.; Chen, F.; Cui, L. COVID-19 and Cognitive Impairment: Neuroinvasive and Blood‒brain Barrier Dysfunction. J. Neuroinflamm. 2022, 19, 222. [Google Scholar] [CrossRef] [PubMed]
  24. Matschke, J.; Lütgehetmann, M.; Hagel, C.; Sperhake, J.P.; Schröder, A.S.; Edler, C.; Mushumba, H.; Fitzek, A.; Allweiss, L.; Dandri, M.; et al. Neuropathology of Patients with COVID-19 in Germany: A Post-Mortem Case Series. Lancet Neurol. 2020, 19, 919–929. [Google Scholar] [CrossRef]
  25. Erickson, M.A.; Banks, W.A. Neuroimmune Axes of the Blood-Brain Barriers and Blood-Brain Interfaces: Bases for Physiological Regulation, Disease States, and Pharmacological Interventions. Pharmacol. Rev. 2018, 70, 278–314. [Google Scholar] [CrossRef] [PubMed]
  26. Marchi, N.; Rasmussen, P.; Kapural, M.; Fazio, V.; Kight, K.; Mayberg, M.R.; Kanner, A.; Ayumar, B.; Albensi, B.; Cavaglia, M.; et al. Peripheral Markers of Brain Damage and Blood-Brain Barrier Dysfunction. Restor. Neurol. Neurosci. 2003, 21, 109–121. [Google Scholar] [CrossRef] [PubMed]
  27. Yuan, S.; Liu, K.J.; Qi, Z. Occludin Regulation of Blood-Brain Barrier and Potential Therapeutic Target in Ischemic Stroke. Brain Circ. 2020, 6, 152–162. [Google Scholar] [CrossRef]
  28. DeKosky, S.T.; Kochanek, P.M.; Valadka, A.B.; Clark, R.S.B.; Chou, S.H.-Y.; Au, A.K.; Horvat, C.; Jha, R.M.; Mannix, R.; Wisniewski, S.R.; et al. Blood Biomarkers for Detection of Brain Injury in COVID-19 Patients. J. Neurotrauma 2021, 38, 1–43. [Google Scholar] [CrossRef]
  29. Marten, N.W.; Zhou, J. The Role of Metalloproteinases in Corona Virus Infection. In Experimental Models of Multiple Sclerosis; Springer: Boston, MA, 2005; pp. 839–848. [Google Scholar]
  30. Kempuraj, D.; Aenlle, K.K.; Cohen, J.; Mathew, A.; Isler, D.; Pangeni, R.P.; Nathanson, L.; Theoharides, T.C.; Klimas, N.G. COVID-19 and Long COVID: Disruption of the Neurovascular Unit, Blood-Brain Barrier, and Tight Junctions. Neuroscientist 2024, 30, 421–439. [Google Scholar] [CrossRef]
  31. Coelho, S.V.A.; e Souza, G.L.; Bezerra, B.B.; Lima, L.R.; Correa, I.A.; de Almeida, D.V.; da Silva-Aguiar, R.P.; Pinheiro, A.A.S.; Sirois, P.; Caruso-Neves, C.; et al. SARS-CoV-2 Replication in a Blood–Brain Barrier Model Established with Human Brain Microvascular Endothelial Cells Induces Permeability and Disables ACE2-Dependent Regulation of Bradykinin B1 Receptor. Int. J. Mol. Sci. 2025, 26, 5540. [Google Scholar] [CrossRef]
  32. Nalbandian, A.; Sehgal, K.; Gupta, A.; Madhavan, M.V.; McGroder, C.; Stevens, J.S.; Cook, J.R.; Nordvig, A.S.; Shalev, D.; Sehrawat, T.S.; et al. Post-Acute COVID-19 Syndrome. Nat. Med. 2021, 27, 601–615. [Google Scholar] [CrossRef]
  33. Monje, M.; Iwasaki, A. The Neurobiology of Long COVID. Neuron 2022, 110, 3484–3496. [Google Scholar] [CrossRef]
  34. Kubota, T.; Kuroda, N.; Sone, D. Neuropsychiatric Aspects of Long COVID: A Comprehensive Review. Psychiatry Clin. Neurosci. 2023, 77, 84–93. [Google Scholar] [CrossRef]
  35. Fernández-de-Las-Peñas, C.; Palacios-Ceña, D.; Gómez-Mayordomo, V.; Cuadrado, M.L.; Florencio, L.L. Defining Post-COVID Symptoms (Post-Acute COVID, Long COVID, Persistent Post-COVID): An Integrative Classification. Int. J. Environ. Res. Public. Health 2021, 18, 2621. [Google Scholar] [CrossRef]
  36. National Institute for Health and Care Excellence (NICE); Scottish Intercollegiate Guidelines Network (SIGN); Royal College of General Practitioners (RCGP). COVID-19 Rapid Guideline: Managing the Long-Term Effects of COVID-19; National Institute for Health and Care Excellence: London, UK, 2020. [Google Scholar]
  37. Alemanno, F.; Houdayer, E.; Parma, A.; Spina, A.; Del Forno, A.; Scatolini, A.; Angelone, S.; Brugliera, L.; Tettamanti, A.; Beretta, L.; et al. COVID-19 Cognitive Deficits after Respiratory Assistance in the Subacute Phase: A COVID-Rehabilitation Unit Experience. PLoS ONE 2021, 16, e0246590. [Google Scholar] [CrossRef] [PubMed]
  38. Ermis, U.; Rust, M.I.; Bungenberg, J.; Costa, A.; Dreher, M.; Balfanz, P.; Marx, G.; Wiesmann, M.; Reetz, K.; Tauber, S.C.; et al. Neurological Symptoms in COVID-19: A Cross-Sectional Monocentric Study of Hospitalized Patients. Neurol. Res. Pract. 2021, 3, 17. [Google Scholar] [CrossRef] [PubMed]
  39. Helms, J.; Kremer, S.; Merdji, H.; Clere-Jehl, R.; Schenck, M.; Kummerlen, C.; Collange, O.; Boulay, C.; Fafi-Kremer, S.; Ohana, M.; et al. Neurologic Features in Severe SARS-CoV-2 Infection. N. Engl. J. Med. 2020, 382, 2268–2270. [Google Scholar] [CrossRef]
  40. Hosp, J.A.; Dressing, A.; Blazhenets, G.; Bormann, T.; Rau, A.; Schwabenland, M.; Thurow, J.; Wagner, D.; Waller, C.; Niesen, W.D.; et al. Cognitive Impairment and Altered Cerebral Glucose Metabolism in the Subacute Stage of COVID-19. Brain 2021, 144, 1263–1276. [Google Scholar] [CrossRef] [PubMed]
  41. Kanberg, N.; Simrén, J.; Edén, A.; Andersson, L.-M.; Nilsson, S.; Ashton, N.J.; Sundvall, P.-D.; Nellgård, B.; Blennow, K.; Zetterberg, H.; et al. Neurochemical Signs of Astrocytic and Neuronal Injury in Acute COVID-19 Normalizes during Long-Term Follow-Up. EBioMedicine 2021, 70, 103512. [Google Scholar] [CrossRef]
  42. Almeria, M.; Cejudo, J.C.; Sotoca, J.; Deus, J.; Krupinski, J. Cognitive Profile Following COVID-19 Infection: Clinical Predictors Leading to Neuropsychological Impairment. Brain Behav. Immun. Health 2020, 9, 100163. [Google Scholar] [CrossRef]
  43. Groiss, S.J.; Balloff, C.; Elben, S.; Brandenburger, T.; Müttel, T.; Kindgen-Milles, D.; Vollmer, C.; Feldt, T.; Kunstein, A.; Ole Jensen, B.-E.; et al. Prolonged Neuropsychological Deficits, Central Nervous System Involvement, and Brain Stem Affection After COVID-19—A Case Series. Front. Neurol. 2020, 11, 574004. [Google Scholar] [CrossRef]
  44. Jaywant, A.; Vanderlind, W.M.; Alexopoulos, G.S.; Fridman, C.B.; Perlis, R.H.; Gunning, F.M. Frequency and Profile of Objective Cognitive Deficits in Hospitalized Patients Recovering from COVID-19. Neuropsychopharmacology 2021, 46, 2235–2240. [Google Scholar] [CrossRef]
  45. Méndez, R.; Balanzá-Martínez, V.; Luperdi, S.C.; Estrada, I.; Latorre, A.; González-Jiménez, P.; Feced, L.; Bouzas, L.; Yépez, K.; Ferrando, A.; et al. Short-term Neuropsychiatric Outcomes and Quality of Life in COVID-19 Survivors. J. Intern. Med. 2021, 290, 621–631. [Google Scholar] [CrossRef]
  46. Negrini, F.; Ferrario, I.; Mazziotti, D.; Berchicci, M.; Bonazzi, M.; de Sire, A.; Negrini, S.; Zapparoli, L. Neuropsychological Features of Severe Hospitalized Coronavirus Disease 2019 Patients at Clinical Stability and Clues for Postacute Rehabilitation. Arch. Phys. Med. Rehabil. 2021, 102, 155–158. [Google Scholar] [CrossRef]
  47. Ortelli, P.; Ferrazzoli, D.; Sebastianelli, L.; Engl, M.; Romanello, R.; Nardone, R.; Bonini, I.; Koch, G.; Saltuari, L.; Quartarone, A.; et al. Neuropsychological and Neurophysiological Correlates of Fatigue in Post-Acute Patients with Neurological Manifestations of COVID-19: Insights into a Challenging Symptom. J. Neurol. Sci. 2021, 420, 117271. [Google Scholar] [CrossRef] [PubMed]
  48. Chaumont, H.; Meppiel, E.; Roze, E.; Tressières, B.; de Broucker, T.; Lannuzel, A. Long-Term Outcomes after NeuroCOVID: A 6-Month Follow-up Study on 60 Patients. Rev. Neurol. 2022, 178, 137–143. [Google Scholar] [CrossRef]
  49. Davis, H.E.; Assaf, G.S.; McCorkell, L.; Wei, H.; Low, R.J.; Re’em, Y.; Redfield, S.; Austin, J.P.; Akrami, A. Characterizing Long COVID in an International Cohort: 7 Months of Symptoms and Their Impact. EClinicalMedicine 2021, 38, 101019. [Google Scholar] [CrossRef] [PubMed]
  50. Ferrando, S.J.; Dornbush, R.; Lynch, S.; Shahar, S.; Klepacz, L.; Karmen, C.L.; Chen, D.; Lobo, S.A.; Lerman, D. Neuropsychological, Medical, and Psychiatric Findings After Recovery From Acute COVID-19: A Cross-Sectional Study. J. Acad. Consult. Liaison Psychiatry 2022, 63, 474–484. [Google Scholar] [CrossRef]
  51. Krishnan, K.; Miller, A.K.; Reiter, K.; Bonner-Jackson, A. Neurocognitive Profiles in Patients With Persisting Cognitive Symptoms Associated With COVID-19. Arch. Clin. Neuropsychol. 2022, 37, 729–737. [Google Scholar] [CrossRef]
  52. Pilotto, A.; Cristillo, V.; Cotti Piccinelli, S.; Zoppi, N.; Bonzi, G.; Sattin, D.; Schiavolin, S.; Raggi, A.; Canale, A.; Gipponi, S.; et al. Long-Term Neurological Manifestations of COVID-19: Prevalence and Predictive Factors. Neurol. Sci. 2021, 42, 4903–4907. [Google Scholar] [CrossRef] [PubMed]
  53. García-Sánchez, C.; Calabria, M.; Grunden, N.; Pons, C.; Arroyo, J.A.; Gómez-Anson, B.; Lleó, A.; Alcolea, D.; Belvís, R.; Morollón, N.; et al. Neuropsychological Deficits in Patients with Cognitive Complaints after COVID-19. Brain Behav. 2022, 12, e2508. [Google Scholar] [CrossRef]
  54. Méndez, R.; Balanzá-Martínez, V.; Luperdi, S.C.; Estrada, I.; Latorre, A.; González-Jiménez, P.; Bouzas, L.; Yépez, K.; Ferrando, A.; Reyes, S.; et al. Long-Term Neuropsychiatric Outcomes in COVID-19 Survivors: A 1-Year Longitudinal Study. J. Intern. Med. 2022, 291, 247–251. [Google Scholar] [CrossRef]
  55. Miskowiak, K.W.; Fugledalen, L.; Jespersen, A.E.; Sattler, S.M.; Podlekareva, D.; Rungby, J.; Porsberg, C.M.; Johnsen, S. Trajectory of Cognitive Impairments over 1 Year after COVID-19 Hospitalisation: Pattern, Severity, and Functional Implications. Eur. Neuropsychopharmacol. 2022, 59, 82–92. [Google Scholar] [CrossRef]
  56. Ruzicka, M.; Sachenbacher, S.; Heimkes, F.; Uebleis, A.O.; Karch, S.; Grosse-Wentrup, F.; Fonseca, G.J.I.; Wunderlich, N.; Bogner, J.; Mayerle, J.; et al. Characterization of Cognitive Symptoms in Post COVID-19. Patients 2024, 274, 1923–1934. [Google Scholar] [CrossRef]
  57. Staudt, A.; Jörres, R.A.; Hinterberger, T.; Lehnen, N.; Loew, T.; Budweiser, S. Associations of Post-Acute COVID Syndrome with Physiological and Clinical Measures 10 Months after Hospitalization in Patients of the First Wave. Eur. J. Intern. Med. 2022, 95, 50–60. [Google Scholar] [CrossRef]
  58. Taquet, M.; Skorniewska, Z.; De Deyn, T.; Hampshire, A.; Trender, W.R.; Hellyer, P.J.; Chalmers, J.D.; Ho, L.P.; Horsley, A.; Marks, M.; et al. Cognitive and Psychiatric Symptom Trajectories 2–3 Years after Hospital Admission for COVID-19: A Longitudinal, Prospective Cohort Study in the UK. Lancet Psychiatry 2024, 11, 696–708. [Google Scholar] [CrossRef] [PubMed]
  59. Wood, G.K.; Sargent, B.F.; Ahmad, Z.U.A.; Tharmaratnam, K.; Dunai, C.; Egbe, F.N.; Martin, N.H.; Facer, B.; Pendered, S.L.; Rogers, H.C.; et al. Posthospitalization COVID-19 Cognitive Deficits at 1 Year Are Global and Associated with Elevated Brain Injury Markers and Gray Matter Volume Reduction. Nat. Med. 2024, 31, 245–257. [Google Scholar] [CrossRef]
  60. Miskowiak, K.W.; Pedersen, J.K.; Gunnarsson, D.V.; Roikjer, T.K.; Podlekareva, D.; Hansen, H.; Dall, C.H.; Johnsen, S. Cognitive Impairments among Patients in a Long-COVID Clinic: Prevalence, Pattern and Relation to Illness Severity, Work Function and Quality of Life. J. Affect. Disord. 2023, 324, 162–169. [Google Scholar] [CrossRef] [PubMed]
  61. Thwaites, R.S.; Uruchurtu, A.S.S.; Siggins, M.K.; Liew, F.; Russell, C.D.; Moore, S.C.; Fairfield, C.; Carter, E.; Abrams, S.; Short, C.E.; et al. Inflammatory Profiles across the Spectrum of Disease Reveal a Distinct Role for GM-CSF in Severe COVID-19. Sci. Immunol. 2021, 6, eabg9873. [Google Scholar] [CrossRef] [PubMed]
  62. Lai, Y.J.; Liu, S.H.; Manachevakul, S.; Lee, T.A.; Kuo, C.T.; Bello, D. Biomarkers in Long COVID-19: A Systematic Review. Front. Med. 2023, 10, 1085988. [Google Scholar] [CrossRef]
  63. Chen, X.; Zhao, B.; Qu, Y.; Chen, Y.; Xiong, J.; Feng, Y.; Men, D.; Huang, Q.; Liu, Y.; Yang, B.; et al. Detectable Serum Severe Acute Respiratory Syndrome Coronavirus 2 Viral Load (RNAemia) Is Closely Correlated With Drastically Elevated Interleukin 6 Level in Critically Ill Patients With Coronavirus Disease 2019. Clin. Infect. Dis. 2020, 71, 1937–1942. [Google Scholar] [CrossRef]
  64. Bonetto, V.; Pasetto, L.; Lisi, I.; Carbonara, M.; Zangari, R.; Ferrari, E.; Punzi, V.; Luotti, S.; Bottino, N.; Biagianti, B.; et al. Markers of Blood-Brain Barrier Disruption Increase Early and Persistently in COVID-19 Patients with Neurological Manifestations. Front. Immunol. 2022, 13, 1070379. [Google Scholar] [CrossRef]
  65. Greene, C.; Connolly, R.; Brennan, D.; Laffan, A.; O’Keeffe, E.; Zaporojan, L.; O’Callaghan, J.; Thomson, B.; Connolly, E.; Argue, R.; et al. Blood–Brain Barrier Disruption and Sustained Systemic Inflammation in Individuals with Long COVID-Associated Cognitive Impairment. Nat. Neurosci. 2024, 27, 421–432. [Google Scholar] [CrossRef]
  66. Mouton, W.; Djebali, S.; Villard, M.; Allatif, O.; Chauvel, C.; Benezech, S.; Vanhems, P.; Marvel, J.; Walzer, T.; Trouillet-Assant, S. Immunological and Clinical Markers of Post-acute Sequelae of COVID-19: Insights from Mild and Severe Cases 6 Months Post-infection. Eur. J. Immunol. 2025, 55, e51948. [Google Scholar] [CrossRef]
  67. Peluso, M.J.; Sans, H.M.; Forman, C.A.; Nylander, A.N.; Ho, H.; Lu, S.; Goldberg, S.A.; Hoh, R.; Tai, V.; Munter, S.E.; et al. Plasma Markers of Neurologic Injury and Inflammation in People With Self-Reported Neurologic Postacute Sequelae of SARS-CoV-2 Infection. Neurol. Neuroimmunol. Neuroinflamm. 2022, 9, e200003. [Google Scholar] [CrossRef]
  68. Patterson, B.K.; Guevara-Coto, J.; Yogendra, R.; Francisco, E.B.; Long, E.; Pise, A.; Rodrigues, H.; Parikh, P.; Mora, J.; Mora-Rodríguez, R.A. Immune-Based Prediction of COVID-19 Severity and Chronicity Decoded Using Machine Learning. Front. Immunol. 2021, 12, 700782. [Google Scholar] [CrossRef] [PubMed]
  69. Ong, S.W.X.; Fong, S.W.; Young, B.E.; Chan, Y.H.; Lee, B.; Amrun, S.N.; Chee, R.S.L.; Yeo, N.K.W.; Tambyah, P.; Pada, S.; et al. Persistent Symptoms and Association with Inflammatory Cytokine Signatures in Recovered Coronavirus Disease 2019 Patients. Open Forum. Infect. Dis. 2021, 8, ofab156. [Google Scholar] [CrossRef]
  70. Schultheiß, C.; Willscher, E.; Paschold, L.; Gottschick, C.; Klee, B.; Henkes, S.-S.; Bosurgi, L.; Dutzmann, J.; Sedding, D.; Frese, T.; et al. The IL-1β, IL-6, and TNF Cytokine Triad Is Associated with Post-Acute Sequelae of COVID-19. Cell Rep. Med. 2022, 3, 100663. [Google Scholar] [CrossRef] [PubMed]
  71. Nuber-Champier, A.; Breville, G.; Voruz, P.; Jacot de Alcântara, I.; Cionca, A.; Allali, G.; Lalive, P.H.; Benzakour, L.; Lövblad, K.-O.; Braillard, O.; et al. Systemic Cytokines Related to Memory Function 6–9 Months and 12–15 Months after SARS-CoV-2 Infection. Sci. Rep. 2024, 14, 22660. [Google Scholar] [CrossRef]
  72. Colarusso, C.; Maglio, A.; Terlizzi, M.; Vitale, C.; Molino, A.; Pinto, A.; Vatrella, A.; Sorrentino, R. Post-COVID-19 Patients Who Develop Lung Fibrotic-like Changes Have Lower Circulating Levels of IFN-β but Higher Levels of IL-1α and TGF-β. Biomedicines 2021, 9, 1931. [Google Scholar] [CrossRef] [PubMed]
  73. Kwon, J.S.; Chang, E.; Jang, H.M.; Kim, J.Y.; Kim, W.; Son, J.Y.; Cha, J.; Jang, C.Y.; Bae, S.; Jung, J.; et al. Cytokine Profiles Associated with Persisting Symptoms of Post-Acute Sequelae of COVID-19. Korean J. Intern. Med. 2025, 40, 667–675. [Google Scholar] [CrossRef]
  74. Wechsler, J.B.; Butuci, M.; Wong, A.; Kamboj, A.P.; Youngblood, B.A. Mast Cell Activation Is Associated with Post-Acute COVID-19 Syndrome. Allergy Eur. J. Allergy Clin. Immunol. 2022, 77, 1288–1291. [Google Scholar] [CrossRef]
  75. Zhao, J.; Schank, M.; Wang, L.; Dang, X.; Cao, D.; Khanal, S.; Nguyen, L.N.T.; Zhang, Y.; Wu, X.Y.; Adkins, J.L.; et al. Plasma Biomarkers for Systemic Inflammation in COVID-19 Survivors. Proteomics Clin. Appl. 2022, 16, 2200031. [Google Scholar] [CrossRef] [PubMed]
  76. Ramezani, S.; Ezzatifar, F.; Hojjatipour, T.; Hemmatzadeh, M.; Shabgah, A.G.; Navashenaq, J.G.; Aslani, S.; Shomali, N.; Arabi, M.; Babaie, F.; et al. Association of the Matrix Metalloproteinases (MMPs) Family Gene Polymorphisms and the Risk of Coronavirus Disease 2019 (COVID-19); Implications of Contribution for Development of Neurological Symptoms in the COVID-19 Patients. Mol. Biol. Rep. 2023, 50, 173–183, Correction in Mol. Biol. Rep. 2023, 50, 10679–10680. https://doi.org/10.1007/s11033-022-07907-y.. [Google Scholar] [CrossRef] [PubMed]
  77. Hanson, B.A.; Visvabharathy, L.; Ali, S.T.; Kang, A.K.; Patel, T.R.; Clark, J.R.; Lim, P.H.; Orban, Z.S.; Hwang, S.S.; Mattoon, D.; et al. Plasma Biomarkers of Neuropathogenesis in Hospitalized Patients With COVID-19 and Those with Postacute Sequelae of SARS-CoV-2 Infection. Neurol. Neuroimmunol. Neuroinflamm. 2022, 9, e1151. [Google Scholar] [CrossRef] [PubMed]
  78. Cavalcante, G.L.; Bonifacio, L.P.; Sanches-lopes, J.M.; Puga, F.G.; de Carvalho, F.S.; Bellissimo-Rodrigues, F.; Tanus-Santos, J.E. Matrix Metalloproteinases Are Associated with Severity of Disease among COVID-19 Patients: A Possible Pharmacological Target. Basic. Clin. Pharmacol. Toxicol. 2024, 134, 727–736. [Google Scholar] [CrossRef]
  79. Telser, J.; Grossmann, K.; Weideli, O.C.; Hillmann, D.; Aeschbacher, S.; Wohlwend, N.; Velez, L.; Kuhle, J.; Maleska, A.; Benkert, P.; et al. Concentrations of Serum Brain Injury Biomarkers Following SARS-CoV-2 Infection in Individuals with and without Long-COVID—Results from the Prospective Population-Based COVI-GAPP Study. Diagnostics 2023, 13, 2167. [Google Scholar] [CrossRef]
  80. Magdy, R.; Eid, R.A.; Fathy, W.; Abdel-Aziz, M.M.; Ibrahim, R.E.; Yehia, A.; Sheemy, M.S.; Hussein, M. Characteristics and Risk Factors of Persistent Neuropathic Pain in Recovered COVID-19 Patients. Pain. Med. 2022, 23, 774–781. [Google Scholar] [CrossRef]
  81. Wallensten, J.; Havervall, S.; Power, Y.; Åsberg, M.; Borg, K.; Nager, A.; Thålin, C.; Mobarrez, F. Oneyear Longitudinal Study on Biomarkers of Blood–Brain Barrier Permeability in COVID-19 Patients. Sci. Rep. 2024, 14, 22735. [Google Scholar] [CrossRef]
  82. Volk, P.; Rahmani Manesh, M.; Warren, M.E.; Besko, K.; Gonçalves de Andrade, E.; Wicki-Stordeur, L.E.; Swayne, L.A. Long-term Neurological Dysfunction Associated with COVID-19: Lessons from Influenza and Inflammatory Diseases? J. Neurochem. 2023, 168, 3500–3511. [Google Scholar] [CrossRef]
  83. Clé, M.; Eldin, P.; Briant, L.; Lannuzel, A.; Simonin, Y.; Van de Perre, P.; Cabié, A.; Salinas, S. Neurocognitive Impacts of Arbovirus Infections. J. Neuroinflamm. 2020, 17, 233. [Google Scholar] [CrossRef]
  84. Peuchmaur, M.; Voisin, J.; Vaillant, M.; Truffot, A.; Lupo, J.; Morand, P.; Le Maréchal, M.; Germi, R. Epstein-Barr Virus Encephalitis: A Review of Case Reports from the Last 25 Years. Microorganisms 2023, 11, 2825. [Google Scholar] [CrossRef] [PubMed]
  85. Sozzi, M.; Algeri, L.; Corsano, M.; Crivelli, D.; Daga, M.A.; Fumagalli, F.; Gemignani, P.; Granieri, M.C.; Inzaghi, M.G.; Pala, F.; et al. Neuropsychology in the Times of COVID-19. The Role of the Psychologist in Taking Charge of Patients With Alterations of Cognitive Functions. Front. Neurol. 2020, 11, 573207. [Google Scholar] [CrossRef] [PubMed]
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